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The purpose of this chapter is to solve multi-objective formulation for traveling salesman and transportation problems. Computations are based on real data for the road freight transportation of a Spanish company. The company was selected because of its importance in Spanish economy and market. This company is important in the whole country; however, it has its higher importance in the northern part of Spain. The requirements for these models are the minimization of total distance and the CO₂ emissions. To achieve this, it is required to know and carry out the minimization of the total distance traveled by the trucks during the deliveries. The deliveries are going to be executed between the different locations, nodes, in the region, and Elorrio, where the depot is situated. The data have been used to decide the best route in order to obtain a minimization of cost for the company. As it was mentioned earlier, the problems are focused on the reduction of the amount of CO₂ emissions and minimization of total distance; by studying different parameters, the best solutions of route transportation have been obtained. The software used to solve these models is CPLEX solver with AMPL programming language.

The purpose of this paper is to determine a set of routes for multiple salesmen starting at and turning back to the home depots. The objective of the algorithm is to be efficient and to minimize the total cost of all salesmen.

The new method first generates a SModel, then deletes all redundant edges in the model and reorganizes isolated paths. According to the given statistics, about 16.5 percent of the nodes have a degree greater than 2 in the SModel, which means that there must be redundant edges in the model. The authors refer to those edges connected to nodes with a degree greater than 2 as redundant candidate edges. By deleting redundant edges, the original graph is simplified to a great extent, then related operation is adopted to generate expected result.

A simple model is used to simplify the original graphs by deleting redundant edges. Based on the simplified results, two strategies are proposed to determine primal edges linking with home depot. Simulations are carried out to illustrate the performance of the proposed method.

Although new method can efficiently solve the variance of multiple traveling salesmen problem (MTSP) with multiple salesmen open path, it does not consider the workload balance. To a great extent, the total course time of this variance of MTSP is decided by the last achieved salesman's time cost.

This method can be used to simulate many everyday applications such as transportation logistics, job planning, vehicle scheduling, and so on. The main applications include print press scheduling, crew scheduling, school bus routing, mission planning, and the design of global navigation satellite surveying system networks. Moreover, it can be used to solve the problem of multiple traveling robots, and can be considered as a relaxation of the vehicle routing problem (VRP) with the capacity restrictions removed.

This paper proposes a new method to solve a heterogeneous MTSP with multiple depots and open paths. A simple model (SModel) is introduced to implement it. The model can transform a complicated graph into a simplified one. Based on the model, the subsequent workings of the new method involve merely linking paths together. Based on SModel, the greatest advantage of the new method is that it can find a global solution efficiently.

The strength of personal selling lies in the fact that it allows for communicative interchange, a process more subtle but, at the same time, more hazardous than classical methods such as advertising, which rely on one‐way communication. In terms of efficiency, communicative interchange results in a reduction of reach losses; it is of primary importance in the marketing of commodities which have to be explained or demonstrated to the buyer and particularly, therefore, in industrial marketing and the marketing of services. It is recognised, however, that personal selling is a relatively expensive means of communication.The author undertakes a taxonomical review of the various constituents of the personal selling scene, analysing the tasks involved and the composition of the sales force. In the latter half of the monograph he selects certain sales force management problems of special importance to discuss in greater detail with regard to the optimisation of efficiency and job statisfaction.

Scheduling is defined by Baker as, “the allocation of resources over time to perform a collection of tasks”. The term facilities is often used instead of resources and the tasks to be performed may involve a variety of different operations.

This paper aims to define the class of fragment constructive heuristics used to compute feasible solutions for the traveling salesman problem (TSP) into edge-greedy and vertex-greedy subclasses. As these subclasses of heuristics can create subtours, two known methodologies for subtour elimination on symmetric instances are reviewed and are expanded to cover asymmetric problem instances. This paper introduces a third novel subtour elimination methodology, the greedy tracker (GT), and compares it to both known methodologies.

Computational results for all three subtour elimination methodologies are generated across 17 symmetric instances ranging in size from 29 vertices to 5,934 vertices, as well as 9 asymmetric instances ranging in size from 17 to 443 vertices.

The results demonstrate the GT is the fastest method for preventing subtours for instances below 400 vertices. Additionally, a distinction between fragment constructive heuristics and the subtour elimination methodology used to ensure the feasibility of resulting solutions enables the introduction of a new vertex-greedy fragment heuristic called ordered greedy.

This research has two main contributions: first, it introduces a novel subtour elimination methodology. Second, the research introduces the concept of ordered lists which remaps the TSP into a new space with promising initial computational results.

Biogeography‐based optimization algorithm is a new kind of optimization algorithm based on biogeography. It is designed based on the migration strategy of animals to solve the problem of optimization. The purpose of this paper is to present a new algorithm – biogeography migration algorithm for traveling salesman problem (TSPBMA). A new special migration operator is designed for producing new solutions.

The paper gives the definition of TSP and models of TSPBMA; introduces the algorithm of TSPBMA in detail and gives the proof of convergence in theory; provides simulation results of TSPBMA compared with other optimization algorithms for TSP and presents some concluding remarks and suggestions for further work.

The TSPBMA is tested on some classical TSP problems. The comparison results with the other nature‐inspired optimization algorithms show that TSPBMA is useful for TSP combination optimization. Especially, the designed migration operator is very effective for TSP solving. Although the proposed TSPBMA is not better than ant colony algorithm in the respect of convergence speed and accuracy, it provides a new way for this kind of problem.

The migration operator is a new strategy for solving TSPs. It has never been used by any other evolutionary algorithm or swarm intelligence before TSPBMA.

The success of business process re‐engineering (BPR) is dependent on the use of data‐driven methods that provide cost‐effective and optimal solutions. Today's business managers are inundated with methodologies and tools that claim to provide sustaining process improvement results. Determining the appropriate BPR method(s) to employ is a daunting task for many businesses. Understanding the technical complexities of these methods is even more overwhelming. However, with the increased availability of management science software, business managers can easily identify and employ proven management science techniques. Readily available software that provides timely results, is easily adaptable to resource changes, and does not require extensive technical competencies. This paper demonstrates how scientific management techniques, coupled with management science software (Management Scientist, Project Management and Excel), provided a feasible and achievable solution to a laboratory courier service BPR project. The solution yields a 19.5 percent reduction in annual laboratory courier specimen costs while improving service levels.

This study aims to propose an efficient dual-robot task collaboration strategy to address the issue of low work efficiency and inability to meet the production needs of a single robot during construction operations.

A hybrid task allocation method based on integer programming and auction algorithms, with the aim of achieving a balanced workload between two robots has been proposed. In addition, while ensuring reasonable workload allocation between the two robots, an improved dual ant colony algorithm was used to solve the dual traveling salesman problem, and the global path planning of the two robots was determined, resulting in an efficient and collision-free path for the dual robots to operate. Meanwhile, an improved fast Random tree rapidly-exploring random tree algorithm is introduced as a local obstacle avoidance strategy.

The proposed method combines randomization and iteration techniques to achieve an efficient task allocation strategy for two robots, ensuring the relative optimal global path of the two robots in cooperation and solving complex local obstacle avoidance problems.

This method is applied to the scene of steel bar tying in construction work, with the workload allocation and collaborative work between two robots as evaluation indicators. The experimental results show that this method can efficiently complete the steel bar banding operation, effectively reduce the interference between the two robots and minimize the interference of obstacles in the environment.

Liquefied petroleum gas (LPG) transportation risks depend on aspects such as the total length of the trip and population density along the route. Choosing to deliver the product on non-busy days and reducing distances travelled may help to reduce these risks and lower the level of air pollution generated by the transportation trucks. The purpose of this paper is to reduce LPG delivery impact.

A three-stage methodology is proposed. First, rules are created in order to choose which clients have to be visited each day to avoid deliveries in downtown areas during business days. Second, an Iterated Local Search (ILS) metaheuristic is proposed for the capacitated p-median problem to group the chosen customers. Finally, another ILS is proposed to solve the Travelling Salesman Problem, for each truck to follow a better route while visiting its customers.

The methodology resulted in a 24.8 per cent reduction in distances travelled, representing an annual reduction of 32,716 kg in CO₂ emissions. The average amount of product sold per kilometre travelled improved by 72 per cent.

The literature shows a clear need for companies to consider sustainability in their daily decisions. However, especially in developing countries, there is a fear that protecting the environment may cost money. This main contribution of this paper is that it presents a real solution, serving as a guide for companies to improve their transportation system, resulting in environmental and economic benefits.